Search

Content Types

Subjects

Authors

Research Themes

JEL Codes

Sources

Published After

Published Before

106 Results

Estimation and Inference for Stochastic Volatility Models with Heavy-Tailed Distributions

Statistical inference--both estimation and testing--for stochastic volatility (SV) models is known to be challenging and computationally demanding. We propose simple and efficient estimators for SV models with conditionally heavy-tailed error distributions, particularly the Student’s t and Generalized Exponential Distributions (GED). The estimators rely on a small set of moment conditions derived from ARMA-type representations of SV models, with an option to apply “winsorization” to improve stability and finite-sample performance. Except for the degrees of-freedom parameter, closed-form expressions are available for all other parameters, extending Ahsan and Dufour (2019, 2021), thus eliminating the need for numerical optimization or initial values. We derive the estimators’ asymptotic distribution and show that, due to their analytical tractability, they support reliable, and even exact, simulation-based inference via Monte Carlo or bootstrap methods. We assess their performance through extensive simulations and demonstrate their practical relevance in financial return data, which strongly reject the normality assumption in favor of heavy-tailed models.

Do Monetary Policy Shocks Affect the Neutral Rate of Interest?

Staff working paper 2026-6 Danilo Leiva-Leon, Rodrigo Sekkel, Luis Uzeda
Can monetary policy influence the neutral real interest rate (r-star)? Using a new statistical model, we show that interest rate hikes tend to lower r-star and long-run growth, but that monetary policy explains only a small share of the long-run decline in r-star.

The Sectoral Origins of Post-Pandemic Inflation

Staff working paper 2025-37 Jan David Schneider
This paper quantifies the contribution of sector-specific supply and demand shocks to personal consumption expenditure (PCE) inflation. It derives identification restrictions that are consistent with a large class of dynamic stochastic general equilibrium models with production networks.

Pulse check: Measuring underlying inflation and its drivers

Staff analytical note 2025-29 Luis Uzeda
This note presents PULSE, a new measure of underlying inflation in Canada based on a dynamic factor model estimated on disaggregated inflation data. PULSE captures the persistent component of inflation and decomposes it into broad-based and sector-specific inflationary pressures.

Perceived interconnections between Canadian banks and non-bank financial intermediaries under stress

Staff analytical note 2025-26 Javier Ojea Ferreiro
I study the links between Canadian banks and non-bank financial intermediaries (NBFIs) by observing co-movements in stock prices. Perceived interconnections increased before the COVID-19 pandemic but have since stabilized, with the strongest ties seen between large banks and NBFIs. The secured credit line extended to Home Trust, a non-bank mortgage lender that experienced severe funding stress in 2017, significantly reduced banks' risk exposure to NBFIs during this episode.

A Market-Based Approach to Reverse Stress Testing the Financial System

Staff working paper 2025-32 Javier Ojea Ferreiro
This article examines what market conditions lead to extreme losses in global financial systems. Using a reverse stress testing approach, it introduces two measures of systemic risk by starting from the tail losses and working backward to identify the events most closely associated with them.

Simulating the Resilience of the Canadian Banking Sector Under Stress: An Update of the Bank of Canada’s Top-Down Solvency Assessment Tool

We present a technical description of the Top-Down Solvency Assessment (TDSA) tool. As a solvency stress-testing tool, TDSA is used to assess the banking sector’s capital resilience to hypothetical future risk scenarios.

Financial Shocks and the Output Growth Distribution

This paper studies how financial shocks shape the distribution of output growth by introducing a quantile-augmented vector autoregression (QAVAR), which integrates quantile regressions into a structural VAR framework. The QAVAR preserves standard shock identification while delivering flexible, nonparametric forecasts of conditional moments and tail risk measures for gross domestic product.

The impact of trading flows on Government of Canada bond prices

Staff analytical note 2025-20 Andreas Uthemann, Rishi Vala, Jun Yang
Trading flows affect Government of Canada bond prices. Our estimates suggest a sale of 1% of the available supply of bonds typically lowers bond prices by 0.2%. From 2000 to 2025, demand from institutional investors, such as Canadian pension funds and foreign investors, explains 69% of quarterly price variation, with the remainder explained by changes in the supply of bonds.

Estimating the inflation risk premium

Staff analytical note 2025-9 Bruno Feunou, Gitanjali Kumar
Is there a risk of de-anchoring of inflation expectations in the near term? We estimate the inflation risk premium using traditional asset pricing models to answer this question. The risk of de-anchoring is elevated compared with the period before the COVID-19 pandemic and is higher in the United States than in Canada.
Go To Page